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Data Engineer III
Twenty80 llcRancho Cucamonga
Work Model: Hybrid (onsite 3–4 days per week, Southern California – commutable distance to 91730)Minimum Experience: 6–8 years data engineering, data platform, or related software/data infrastructure
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Data Engineer III
- Rancho Cucamonga, California, United States
- Rancho Cucamonga, California, United States
À propos
Minimum Experience: 6–8 years data engineering, data platform, or related software/data infrastructure experience
Role Summary Our client, a healthcare organization with a strong emphasis on data-driven decision-making and regulatory compliance, is seeking a Data Engineer (Level II or III). This role is responsible for designing, building, and maintaining scalable data solutions that support enterprise data platforms and analytics needs.
The Data Engineer will lead the development of data pipelines, transformation logic, and data architecture while ensuring solutions are secure, efficient, and aligned with organizational standards. The role requires close collaboration with cross-functional teams to support business and member data needs, improve data quality, and enable advanced analytics capabilities.
This position is expected to serve as a technical leader, providing guidance on best practices, reviewing code, and mentoring junior engineers where applicable.
Key Responsibilities Data Engineering & Architecture
Design, develop, and implement scalable and reliable data solutions based on business requirements
Build and maintain data pipeline architectures aligned with security, performance, and scalability standards
Develop and support data transformation processes and data integration workflows
Contribute to data architecture design and maintain documentation such as data flow diagrams, process maps, and technical design documents
Identify trends in datasets and develop logic or algorithms to improve data usability and insights
Data Platforms & Cloud Engineering
Design and deploy cloud-based data solutions, particularly within Azure data services (e.g., Data Lake, Data Factory, Synapse, Azure SQL, Cosmos DB)
Build and optimize large-scale data warehouses and data pipelines
Work with relational and non-relational databases (e.g., SQL Server, MongoDB or similar NoSQL platforms)
Integrate and manage data from multiple sources including APIs and external systems
Development & Automation
Develop complex scripts, functions, and services supporting data engineering and data services teams
Work with programming and scripting languages such as Python, Java, C#, SQL, JSON, and XML
Implement DevOps practices and CI/CD pipelines using tools such as Azure DevOps, GitHub, or GitLab
Automate manual processes and improve data delivery and infrastructure efficiency
Data Quality, Governance & Support
Perform root cause analysis on data issues and implement corrective and preventive solutions
Ensure data solutions meet privacy, compliance, and performance requirements (especially in healthcare context)
Support data mapping, data quality improvement, and system integration efforts
Apply applicable data privacy standards and regulatory considerations
Collaboration & Leadership
Work closely with engineering, data, and business teams to deliver enterprise data solutions
Conduct code reviews and ensure adherence to coding and design standards
Mentor junior engineers (Level I/II) as applicable
Communicate technical concepts clearly to stakeholders and management
Serve as a subject matter expert on key data initiatives and projects
Required Qualifications
6–8 years of experience in data engineering, data platforms, or related software engineering roles
Strong experience designing and building scalable data pipelines and data warehouse solutions
4–8 years of experience working with relational databases (e.g., SQL Server) and data modeling
Strong programming skills in at least one of the following: Python, Java, or C# (plus SQL required)
Experience with cloud data platforms, particularly Azure (Data Lake, Data Factory, Synapse, Cosmos DB or similar)
Experience with CI/CD pipelines and source control tools (GitHub, GitLab, or Azure DevOps)
Strong understanding of SDLC methodologies (Agile, Scrum, Kanban, Waterfall)
Experience working with APIs, data ingestion, and integration workflows
Strong analytical, debugging, and root cause analysis skills
Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or related field
Preferred Qualifications
Experience with healthcare data environments or regulated industries
Familiarity with HL7 / FHIR standards
Experience with stream processing or messaging systems
Experience with big data tools and distributed systems
Experience with ERD design and data modeling tools (e.g., Visio or similar)
Compensation & Work Model
Full-time, direct hire position
Hybrid schedule with onsite work required 3–4 days per week (Southern California, near 91730)
Role includes technical leadership responsibilities, including mentoring and code review
Must be authorized to work in the United States (no sponsorship available)
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Compétences linguistiques
- English
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